Upload README.md

README.md

@@ -1,3 +1,64 @@
 ---
 license: apache-2.0
+library_name: pytorch
+tags:
+  - ocr
+  - text-detection
+  - text-recognition
+  - easyocr
+  - craft
+  - safetensors
 ---
+
+# EasyOCR weights (CRAFT detector and English recogniser) in safetensors
+
+The two pretrained models the [EasyOCR](https://github.com/JaidedAI/EasyOCR) `en` reader uses, converted from the
+official `.pth` files to `.safetensors`. Nothing was retrained or modified: every tensor is identical, in value and dtype,
+to the original, and the key names (including the `module.` prefix) are unchanged.
+
+| File | Model | Tensors | SHA-256 |
+|---|---|---|---|
+| `craft_mlt_25k.safetensors` | CRAFT text detector | 154 | `4ab7f69bd8161b437f18f1718b8f6e58136bd081639f238b567e987415c20268` |
+| `english_g2.safetensors` | English recogniser (CRNN, "generation 2") | 44 | `307a47690148280d00e4314b1868ebce44089d0974903a56fe7822902d1b31d0` |
+
+`SHA256SUMS` lists the same values: `sha256sum -c SHA256SUMS`.
+
+## Origin
+
+Converted from the official EasyOCR release assets (EasyOCR's own MD5 values in `easyocr/config.py` are shown):
+
+| Original | Release asset | MD5 of the original `.pth` |
+|---|---|---|
+| `craft_mlt_25k.pth` | https://github.com/JaidedAI/EasyOCR/releases/download/pre-v1.1.6/craft_mlt_25k.zip | `2f8227d2def4037cdb3b34389dcf9ec1` |
+| `english_g2.pth` | https://github.com/JaidedAI/EasyOCR/releases/download/v1.3/english_g2.zip | `5864788e1821be9e454ec108d61b887d` |
+
+Conversion: `torch.load(..., weights_only=True)` of the state dict, then `safetensors.torch.save_file`. The saved file was
+loaded back and compared tensor by tensor with the original (all equal). An EasyOCR reader fed these tensors returned the
+same boxes, text and confidences as the original reader on the test images it was checked with (CPU).
+
+## Use
+
+These are state dicts, not a ready `easyocr.Reader` folder: EasyOCR itself only looks for MD5-checked `.pth` files, so the
+detector and recogniser have to be built from the state dicts by the caller.
+
+```python
+from safetensors.torch import load_file
+
+craft = load_file("craft_mlt_25k.safetensors")   # CRAFT state dict (keys start with "module.")
+recog = load_file("english_g2.safetensors")      # recogniser state dict (keys start with "module.")
+```
+
+## Licence and attribution
+
+The files are redistributed under the licences of the projects they come from. Keep these notices with them.
+
+- **EasyOCR**, JaidedAI: Apache License 2.0. https://github.com/JaidedAI/EasyOCR
+- **CRAFT** (`craft_mlt_25k`), Clova AI Research, NAVER Corp.: MIT License. https://github.com/clovaai/CRAFT-pytorch.
+  Paper: Baek et al., "Character Region Awareness for Text Detection", CVPR 2019 (https://arxiv.org/abs/1904.01941).
+  EasyOCR ships Clova AI's pretrained CRAFT model.
+- **Recognition training pipeline**, a modified version of `clovaai/deep-text-recognition-benchmark`: Apache License 2.0.
+  https://github.com/clovaai/deep-text-recognition-benchmark. Model architecture: CRNN (Shi et al., 2015).
+
+The upstream projects publish licences for their code. The weight files carry no separate licence statement that was found,
+so they are assumed to follow the repositories above. This repository is an unofficial conversion and is not affiliated
+with JaidedAI or Clova AI.